Learning project for MCTS. This code aims for some efficiency and is strong enough to play well or better against other libraries. I use it in my Nego project.
Current features:
- UCT / UCB1Tuned
- RAVE/GRAVE
- MAST
- Decisive Moves
- Transposition tables
- Hyperparameter tuning with SMAC3
- Arena allocation (just a
Vec, inspired by indextree) - Preliminary benchmarking tools
- A growing number of game implementations
Some things I would like to explore:
- Better testability, ergonomics, safety
- More simulation strategies, selection improvements, etc.
- Online tuning
Other alternatives in Rust:
- minimax-rs: lock-free tree parallel implementation. Better for low branching factor tactical games due to use of full node expansion strategy and reliance on MCTS-Solver.
- ggpf: implements a lot of stuff, including AlphaZero and MuZero TF integration. Supports RAVE, PUCT, etc.
- zxqfl/mcts: some pretty clean looking code with lots of atomics and support for transposition tables. From the author of TabNine. I think it has a lot of good ideas on how to parameterize and mix different strategies.
- recon_mcts: mostly focused on parallelism, with some clever strategies to combine tree results.
- arbor: vanilla MCTS, but with a focus on single threaded efficiency, uses hand maintained arena. Has some transposition support, but says it is experimental. I haven't looked deeply because the project doesn't provide a LICENSE.
- OxyMcts: seems to be a vanilla UCT client
Some code and general approaches come from minimax-rs which has an MCTS strategy.
Not sure if this will become a published library, but it is improving and PRs are welcome.